MAP Prior
for (res in list(res1, res3, res5)){
cat("probability of claiming efficacy is", res$prob_rej, "\n",
"effective historical sample size is", formatC(res$EHSS, digits = 2, format = "f"), "\n",
"Mean Width of Credible Interval for Control Prior", formatC(res$width_quantile_interval_mean, digits = 4, format = "f"), "\n",
"% of times muc is in quantile interval is", formatC(res$quantile_interval_count_mean*100, digits = 4, format = "f"), "\n",
"Bias of point estiamtor based on control prior", formatC(res$bias_point_est, digits = 4, format = "f"), "\n",
"Variance value of point estiamtor based on control prior", formatC(res$var_point_est, digits = 4, format = "f"), "\n",
"MSE of point estiamtor based on control prior", formatC(res$mse_point_est, digits = 4, format = "f"), "\n",
"total time for", 100, "simulations is", formatC(res$time_diff, digits = 4, format = "f"), "\n",
"power:", formatC(res$power, digits = 4, format = "f"))
print(res$plot_density)
print(res$plot_comp)
}
## probability of claiming efficacy is 0
## effective historical sample size is 73.04
## Mean Width of Credible Interval for Control Prior 0.5006
## % of times muc is in quantile interval is 100.0000
## Bias of point estiamtor based on control prior -0.0054
## Variance value of point estiamtor based on control prior 0.0044
## MSE of point estiamtor based on control prior 0.0044
## total time for 100 simulations is 0.7360
## power: 0.8800
## probability of claiming efficacy is 0
## effective historical sample size is 73.04
## Mean Width of Credible Interval for Control Prior 0.5008
## % of times muc is in quantile interval is 97.0000
## Bias of point estiamtor based on control prior 0.1280
## Variance value of point estiamtor based on control prior 0.0044
## MSE of point estiamtor based on control prior 0.0208
## total time for 100 simulations is 0.6228
## power: 0.6700
## probability of claiming efficacy is 0
## effective historical sample size is 73.04
## Mean Width of Credible Interval for Control Prior 0.5081
## % of times muc is in quantile interval is 15.0000
## Bias of point estiamtor based on control prior 0.3280
## Variance value of point estiamtor based on control prior 0.0044
## MSE of point estiamtor based on control prior 0.1119
## total time for 100 simulations is 0.5466
## power: 0.1900
Power Prior
for (res in list(res1, res3, res5)){
cat("probability of claiming efficacy is", res$prob_rej, "\n",
"effective historical sample size is", formatC(res$EHSS, digits = 2, format = "f"), "\n",
"Mean Width of Credible Interval for Control Prior", formatC(res$width_quantile_interval_mean, digits = 4, format = "f"), "\n",
"% of times muc is in quantile interval is", formatC(res$quantile_interval_count_mean*100, digits = 4, format = "f"), "\n",
"Bias of point estiamtor based on control prior", formatC(res$bias_point_est, digits = 4, format = "f"), "\n",
"Variance value of point estiamtor based on control prior", formatC(res$var_point_est, digits = 4, format = "f"), "\n",
"MSE of point estiamtor based on control prior", formatC(res$mse_point_est, digits = 4, format = "f"), "\n",
"total time for", 100, "simulations is", formatC(res$time_diff, digits = 4, format = "f"), "\n",
"power:", formatC(res$power, digits = 4, format = "f"))
print(res$plot_density)
print(res$plot_comp)
}
## probability of claiming efficacy is 0
## effective historical sample size is 68.08
## Mean Width of Credible Interval for Control Prior 0.5163
## % of times muc is in quantile interval is 100.0000
## Bias of point estiamtor based on control prior -0.0026
## Variance value of point estiamtor based on control prior 0.0050
## MSE of point estiamtor based on control prior 0.0050
## total time for 100 simulations is 5.1372
## power: 0.8700
## probability of claiming efficacy is 0
## effective historical sample size is 67.93
## Mean Width of Credible Interval for Control Prior 0.5165
## % of times muc is in quantile interval is 97.0000
## Bias of point estiamtor based on control prior 0.1261
## Variance value of point estiamtor based on control prior 0.0051
## MSE of point estiamtor based on control prior 0.0210
## total time for 100 simulations is 5.0992
## power: 0.6700
## probability of claiming efficacy is 0
## effective historical sample size is 67.97
## Mean Width of Credible Interval for Control Prior 0.5245
## % of times muc is in quantile interval is 21.0000
## Bias of point estiamtor based on control prior 0.3189
## Variance value of point estiamtor based on control prior 0.0050
## MSE of point estiamtor based on control prior 0.1067
## total time for 100 simulations is 5.1151
## power: 0.1900
Normalized Power Prior
for (res in list(res1, res3, res5)){
cat("probability of claiming efficacy is", res$prob_rej, "\n",
"effective historical sample size is", formatC(res$EHSS, digits = 2, format = "f"), "\n",
"Mean Width of Credible Interval for Control Prior", formatC(res$width_quantile_interval_mean, digits = 4, format = "f"), "\n",
"% of times muc is in quantile interval is", formatC(res$quantile_interval_count_mean*100, digits = 4, format = "f"), "\n",
"Bias of point estiamtor based on control prior", formatC(res$bias_point_est, digits = 4, format = "f"), "\n",
"Variance value of point estiamtor based on control prior", formatC(res$var_point_est, digits = 4, format = "f"), "\n",
"MSE of point estiamtor based on control prior", formatC(res$mse_point_est, digits = 4, format = "f"), "\n",
"total time for", 100, "simulations is", formatC(res$time_diff, digits = 4, format = "f"), "\n",
"power:", formatC(res$power, digits = 4, format = "f"))
print(res$plot_density)
print(res$plot_comp)
}
## probability of claiming efficacy is 0.02
## effective historical sample size is 29.98
## Mean Width of Credible Interval for Control Prior 0.8075
## % of times muc is in quantile interval is 96.0000
## Bias of point estiamtor based on control prior 0.0522
## Variance value of point estiamtor based on control prior 0.0376
## MSE of point estiamtor based on control prior 0.0404
## total time for 100 simulations is 8.6560
## power: 0.6100
## probability of claiming efficacy is 0.02
## effective historical sample size is 29.86
## Mean Width of Credible Interval for Control Prior 0.8092
## % of times muc is in quantile interval is 94.0000
## Bias of point estiamtor based on control prior 0.0557
## Variance value of point estiamtor based on control prior 0.0379
## MSE of point estiamtor based on control prior 0.0410
## total time for 100 simulations is 8.6268
## power: 0.6100
## probability of claiming efficacy is 0.02
## effective historical sample size is 30.50
## Mean Width of Credible Interval for Control Prior 0.8111
## % of times muc is in quantile interval is 95.0000
## Bias of point estiamtor based on control prior 0.0614
## Variance value of point estiamtor based on control prior 0.0381
## MSE of point estiamtor based on control prior 0.0418
## total time for 100 simulations is 8.6096
## power: 0.6100
Commensurate Power Prior
for (res in list(res1, res3, res5)){
cat("probability of claiming efficacy is", res$prob_rej, "\n",
"effective historical sample size is", formatC(res$EHSS, digits = 2, format = "f"), "\n",
"Mean Width of Credible Interval for Control Prior", formatC(res$width_quantile_interval_mean, digits = 4, format = "f"), "\n",
"% of times muc is in quantile interval is", formatC(res$quantile_interval_count_mean*100, digits = 4, format = "f"), "\n",
"Bias of point estiamtor based on control prior", formatC(res$bias_point_est, digits = 4, format = "f"), "\n",
"Variance value of point estiamtor based on control prior", formatC(res$var_point_est, digits = 4, format = "f"), "\n",
"MSE of point estiamtor based on control prior", formatC(res$mse_point_est, digits = 4, format = "f"), "\n",
"total time for", 100, "simulations is", formatC(res$time_diff, digits = 4, format = "f"), "\n",
"power:", formatC(res$power, digits = 4, format = "f"))
print(res$plot_density)
print(res$plot_comp)
}
## probability of claiming efficacy is 0.02
## effective historical sample size is 29.44
## Mean Width of Credible Interval for Control Prior 0.8085
## % of times muc is in quantile interval is 96.0000
## Bias of point estiamtor based on control prior 0.0590
## Variance value of point estiamtor based on control prior 0.0391
## MSE of point estiamtor based on control prior 0.0426
## total time for 100 simulations is 9.9481
## power: 0.6100
## probability of claiming efficacy is 0.02
## effective historical sample size is 29.44
## Mean Width of Credible Interval for Control Prior 0.8118
## % of times muc is in quantile interval is 94.0000
## Bias of point estiamtor based on control prior 0.0618
## Variance value of point estiamtor based on control prior 0.0390
## MSE of point estiamtor based on control prior 0.0428
## total time for 100 simulations is 9.9022
## power: 0.6000
## probability of claiming efficacy is 0.02
## effective historical sample size is 30.15
## Mean Width of Credible Interval for Control Prior 0.8154
## % of times muc is in quantile interval is 96.0000
## Bias of point estiamtor based on control prior 0.0624
## Variance value of point estiamtor based on control prior 0.0397
## MSE of point estiamtor based on control prior 0.0436
## total time for 100 simulations is 9.9895
## power: 0.5900
Elastic Prior
for (res in list(res1, res3, res5)){
cat("probability of claiming efficacy is", res$prob_rej, "\n",
"effective historical sample size is", formatC(res$EHSS, digits = 2, format = "f"), "\n",
"Mean Width of Credible Interval for Control Prior", formatC(res$width_quantile_interval_mean, digits = 4, format = "f"), "\n",
"% of times muc is in quantile interval is", formatC(res$quantile_interval_count_mean*100, digits = 4, format = "f"), "\n",
"Bias of point estiamtor based on control prior", formatC(res$bias_point_est, digits = 4, format = "f"), "\n",
"Variance value of point estiamtor based on control prior", formatC(res$var_point_est, digits = 4, format = "f"), "\n",
"MSE of point estiamtor based on control prior", formatC(res$mse_point_est, digits = 4, format = "f"), "\n",
"total time for", 100, "simulations is", formatC(res$time_diff, digits = 4, format = "f"), "\n",
"power:", formatC(res$power, digits = 4, format = "f"))
print(res$plot_density)
print(res$plot_comp)
}
## probability of claiming efficacy is 0.02
## effective historical sample size is 48.51
## Mean Width of Credible Interval for Control Prior 0.4970
## % of times muc is in quantile interval is 97.0000
## Bias of point estiamtor based on control prior 0.0122
## Variance value of point estiamtor based on control prior 0.0141
## MSE of point estiamtor based on control prior 0.0142
## total time for 100 simulations is 34.4223
## power: 0.8300
## probability of claiming efficacy is 0.02
## effective historical sample size is 47.53
## Mean Width of Credible Interval for Control Prior 0.5003
## % of times muc is in quantile interval is 92.0000
## Bias of point estiamtor based on control prior 0.1043
## Variance value of point estiamtor based on control prior 0.0162
## MSE of point estiamtor based on control prior 0.0270
## total time for 100 simulations is 34.2883
## power: 0.6900
## probability of claiming efficacy is 0.02
## effective historical sample size is 29.17
## Mean Width of Credible Interval for Control Prior 0.6114
## % of times muc is in quantile interval is 43.0000
## Bias of point estiamtor based on control prior 0.1560
## Variance value of point estiamtor based on control prior 0.0605
## MSE of point estiamtor based on control prior 0.0848
## total time for 100 simulations is 34.1144
## power: 0.4800
